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Abstract Improved observational constraints on the orbital parameters of the low-mass X-ray binary Scorpius X-1 were recently published in Killestein et al. In the process, errors were corrected in previous orbital ephemerides, which have been used in searches for continuous gravitational waves from Sco X-1 using data from the Advanced LIGO detectors. We present the results of a reanalysis of LIGO detector data from the third observing run of Advanced LIGO and Advanced Virgo using a model-based cross-correlation search. The corrected region of parameter space, which was not covered by previous searches, was about 1/3 as large as the region searched in the original O3 analysis, reducing the required computing time. We have confirmed that no detectable signal is present over a range of gravitational-wave frequencies from 25 to 1600 Hz, analogous to the null result of Abbott et al. Our search sensitivity is comparable to that of Abbott et al., who set upper limits corresponding, between 100 and 200 Hz, to an amplitudeh0of about 10−25when marginalized isotropically over the unknown inclination angle of the neutron star’s rotation axis, or less than 4 × 10−26assuming the optimal orientation.
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This content will become publicly available on May 1, 2026
GWPopulation: Hardware agnostic population inference for compact binaries and beyond
Since the first direct detection of gravitational waves by the LIGO–Virgo collaboration in 2015 (B. P. Abbott et al., 2016), the size of the gravitational-wave transient catalog has grown to nearly 100 events (R. Abbott et al., 2023), with the ongoing fourth observing run more than doubling the total number. Extracting astrophysical or cosmological information from these observations is a hierarchical Bayesian inference problem. GWPopulation is designed to provide simple-to-use, robust, and extensible tools for hierarchical inference in gravitational-wave astronomy or cosmology. It has been widely adopted for gravitational-wave astronomy, including producing flagship results for the LIGO-Virgo-KAGRA collaborations (Abac et al., 2024; R. Abbott et al., 2023). While designed to work with observations of compact binary coalescences, GWPopulation may be available to a wider range of hierarchical Bayesian inference problems.
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- Award ID(s):
- 2207758
- PAR ID:
- 10613636
- Publisher / Repository:
- Journal of Open Source Software
- Date Published:
- Journal Name:
- Journal of Open Source Software
- Volume:
- 10
- Issue:
- 109
- ISSN:
- 2475-9066
- Page Range / eLocation ID:
- 7753
- Subject(s) / Keyword(s):
- Hierarchical Bayesian inference software gravitational waves gravitational-wave astronomy
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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